Applying Data Science to Data Science: a deep dive into the best-loved technologies in the world of Data Science in 2020. — Digging in This article takes a look at what the online Data Science community has been writing about over the last couple of years, with an aim of understanding the trends in technology over the course of 2020. …

Getting abstract Over the last decade or two, cloud computing has come to dominate many of the skills and processes needed to develop ‘modern’ software. This is increasingly true for adjacent fields too, including the world of Data Science (among others). One of the trends in this sweeping move towards ‘The Cloud’…

Data scientists: choosing whether to join a startup is a big decision. Here’s some advice to help you figure out whether life at a startup is for you. — This post is (as the title might suggest) inspired by Chip Huyen’s ‘7 reasons not to join a startup and 1 reason to’ post. While reading it, I was reminded of several conversations I’ve had over the last year or so with various ML practitioners inside and outside of startups…

Getting APIs into production can be a bewildering prospect. This post gives you tips and a template for using Flask in production. — What is Flask? If you work in the world of (or a world adjacent to) cloud software and are familiar with Python, the chances are you’ll have come across Flask — the excellent, minimal ‘ micro’ web framework that’s been at the heart of the Python web community for around a decade. It…

Deployment is hard Deploying software regularly and reliably is hard. Deploying software that utilises Machine Learning (ML) models regularly and reliably can be harder still. …

In Part 1 of this series, you saw a few practical examples of how Object-Oriented Programming (OOP) can be used to help you resolve some code design problems. If you missed it, it’s over here: Object-Oriented Programming: A Practical Introduction (Part 1) Object-Oriented Programming is a staple of the modern software engineering toolbox. This article gives a gentle…towardsdatascience.com Right, let’s dig in.

Creating CLIs can help improve accessibility and reuse of your ML pipelines, but they can be a pain to set up. Enter Fire. — What is Fire? A few months ago, I had an enthusiastic outburst in which I expressed my appreciation for a little package called TQDM for creating progress bars. …

What is Streamlit? If you’re familiar with the Data Science software ecosystem in Python, you’ll likely have come across a handful of widely used dashboarding and data visualization tools designed for programmatic usage (e.g. to be embedded in notebooks or to be served as standalone web-apps). For the last few years, the likes…

The power of OOP If you’ve been programming for at least a little while, you’ll likely have come across (and perhaps used) Object Oriented Programming (OOP) concepts and language-features. …